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Learning Python for Data Analysis and Visualization – Course Description

This course is taught by Jose Portilla.

Here is how the course is officially described on its course page on Udemy:

This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science!

You’ll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.

You will also get lifetime access to over 90 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers!

By the end of this course you will:

– Have an understanding of how to program in Python.

– Know how to create and manipulate arrays using numpy and Python.

– Know how to use pandas to create and analyze data sets.

– Know how to use matplotlib and seaborn libraries to create beautiful data visualization.

– Have an amazing portfolio of example python data analysis projects!

– Have an understanding of Machine Learning and SciKit Learn!

With 90+ lectures and over 16 hours of information and more than 80 example python code notebooks, you will be excellently prepared for a future in data science!

What are the requirements?

  • Basic math skills.
  • Have a computer (either Mac, Windows, or Linux)
  • Desire to learn!

What am I going to get from this course?

  • Over 106 lectures and 19.5 hours of content!
  • Have an intermediate skill level of Python programming.
  • Use the iPython Notebook environment for Python
  • Use the numpy library to create and manipulate arrays.
  • Use the pandas module with Python to create and structure data.
  • Learn how to work with various data formats within python, including: JSON,HTML, and MS Excel Worksheets.
  • Create data visualizations using matplotlib and the seaborn modules with python.
  • Have a portfolio of various data analysis projects.

What is the target audience?

  • Anyone interested in learning more about python, data science, or data visualizations.
  • This course is suited for people who have never programmed as well as people already familiar with python.
  • Anyone interested about the rapidly expanding world of data science!

Click here to learn more about this course and read its reviews.

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